An approach is outlined for the treatment of stresses in complex three-dimensional components for the purpose of conducting probabilistic creep-fatigue lifetime assessments. For conventional deterministic assessments, the stress state in a plant component is found using thermal and mechanical (elastic) finite element (FE) models. Key inputs are typically steam temperatures and pressures, with the three principal stress components (PSCs) at the assessment location(s) being the outputs. This paper presents an approach which was developed based on application experience with a tube-plate ligament (TPL) component, for which historical data was available. Though both transient as well as steady-state conditions can have large contributions towards the creep-fatigue damage, this work is mainly concerned with the latter. In a probabilistic assessment, the aim of this approach is to replace time intensive FE runs with a predictive model to approximate stresses at various assessment locations. This is achieved by firstly modelling a wide range of typical loading conditions using FE models to obtain the desire stresses. Based on the results from these FE runs, a probability map is produced and input(s)-output(s) functions are fitted (either using a Response Surface Method or Linear Regression). These models are thereafter used to predict stresses as functions of the input parameter(s) directly. This mitigates running an FE model for every probabilistic trial (of which there typically may be more than 104), an approach which would be computationally prohibitive.
Management of Complex Loading Histories for Use in Probabilistic Creep-Fatigue Damage Assessments
- Views Icon Views
- Share Icon Share
- Search Site
Zentuti, NA, Booker, JD, Bradford, RAW, & Truman, CE. "Management of Complex Loading Histories for Use in Probabilistic Creep-Fatigue Damage Assessments." Proceedings of the ASME 2018 Pressure Vessels and Piping Conference. Volume 1B: Codes and Standards. Prague, Czech Republic. July 15–20, 2018. V01BT01A001. ASME. https://doi.org/10.1115/PVP2018-84400
Download citation file: